一种用于电商应用评分评估的混合可用性方法
A Hybrid Usability Approach for Rating Evaluation of M-Commerce Applications
- University of Central Punjab（中央旁遮普大学）
- University of Lahore（拉合尔大学）
机构由 AI 辅助整理，请以论文原文为准。
AI总结：
本研究针对移动电商应用，提出含8个因素的混合可用性模型，基于向前逐步多元线性回归构建评分预测模型，用5款应用及PRED(x)、K-fold技术验证，以识别影响评分的关键可用性因素。
AI中文摘要：
任何移动应用的成功都依赖于其有用性，而评分被视为衡量这一点的重要指标。本研究聚焦于识别对移动电商（M-commerce）应用评分有显著影响的可用性因素，旨在探索由不同因素及一组标准构成的现有可用性模型，并通过5款知名移动应用（分别为(i)daraz、(ii)shophive、(iii)home shopping、(iv)Symbios、(v)yayvo）对其评分估计能力进行评估。随后，本研究提出一种用于移动电商应用评分预测的混合可用性模型，该初始模型包含(i)可学习性、(ii)一致性、(iii)人为因素、(iv)沟通性、(v)有效性、(vi)可操作性、(vii)效率、(viii)满意度共8个因素，每个因素包含若干标准。基于混合可用性模型的各因素，每款应用收集了40名用户的数据。此外，通过分析混合可用性模型所有因素的各标准，提出了基于向前逐步多元线性回归的评分预测模型，最后采用PRED(x)和K-fold技术对该模型进行评估与验证。
英文摘要：
The success of any mobile application relies on its usefulness and rating is considered as an important measure in this regard. This research work focuses on identifying usability factors, which contribute significantly towards the rating of M-commerce apps. This work intends to explore existing usability models consisting of different factors along with a set of criteria and evaluate in terms of rating estimation by considering 5 well-known mobile applications, namely (i) daraz, (ii) shophive, (iii) home shopping, (iv) Symbios. (v) yayvo. Then, this work provides a hybrid usability model for rating prediction of M-commerce applications. The initial hybrid usability model comprises of (i) learnability, (ii) consistency, (iii) human factors,(iv)communicativeness,(v)effectiveness, (vi) Operability, (vii) efficiency, (viii) satisfaction. Each factor consists of some criteria. Keeping in view the factors of hybrid usability model, the data was collected from 40 users for each application. Furthermore, Forward Stepwise Multiple Linear Regression based rating prediction model is suggested by analyzing each criterion of all factors of hybrid usability model. Finally, the model is assessed and validated by using PRED(x) and K-fold techniques.
